The Power of Advanced Analytics in Banking

The most successful financial institutions are leveraging advanced analytics to grow customer relationships organically. Using internal and external data, customer needs are not just being met, they are being anticipated.

There is a great deal of discussion in banking around the need to deliver personalized, timely and relevant communications and offers that drive customer profitability, satisfaction and loyalty. Unfortunately, there is still a large gap between the aspirations of bank marketers and the ability to deliver on these goals.

The challenge is that while there are affordable and powerful tools available to create powerful omnichannel customer experiences, most bank marketers are using the same outdated data sources and marketing methodologies they have used for decades. For those marketers who do have the right tools at their disposal, many indicate an inability to use these tools effectively.

The consumer’s buying process is no longer linear or predictable. Consumers often start using one channel and switch channels unpredictably due to individual circumstances. Customers want to interact on their terms, expecting advice and recommendations that are similar to what they receive from other digital partners like Google, Amazon, Facebook and Apple. They want an experience where their needs are not just met, but anticipated.

Despite the challenges, the new marketing reality presents an exceptional opportunity for banks and credit unions to build better customer experiences and deeper consumer relationships. As referenced by IBM in two reports, the current state of marketing is both “the best of times and the worst of times,” where being a marketer has never been more exciting.

To capitalize on opportunities, banks must leverage the wealth of informational assets at their disposal. They must analyze structured and unstructured customer data, and deliver real-time insights that result in unique and compelling opportunities for customer engagement. Most importantly, they must provide advice and solutions across multiple channels.

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Advanced Analytics and the ‘Segment-of-One’

”Traditional analytics provides a great “rear-view mirror” perspective of what has happened. Advanced analytics provides a “GPS” perspective of opportunities ahead.”

No two customers are exactly alike. Beyond traditional demographics, transactions, product holdings and service preferences, marketers can now access online activity logs, call-center interactions, direct feedback and social media usage to build a “segment-of-one” profile. But, analyzing all of this internal and external data requires converting data into actionable insights, which is made more difficult due to silos and the impact of locational data.

Beyond developing great internal reports, bank marketers must apply these big data insights for the benefit of the customer. This includes not only providing real-time advice and solutions, but also anticipating future financial needs on a customer level. Financial institutions must also determine the best way to connect with customers to create a win-win opportunity.

As the volume of data has increased exponentially, the consequences of not leveraging insight has never been more pronounced. Ineffective marketing, dissatisfied customers, missed opportunities and reduced wallet share and loyalty are the costs of not communicating to each customer in a personalized manner. While traditional analytics provide a great “rear-view mirror” perspective of what has happened, advanced analytics provides a “GPS” perspective of opportunities ahead.

According to IBM, the benefits of advanced analytics include:

  • Targeting customers with highly relevant offers across online and offline channels
  • Understanding customers in the context of their relationship with your brand
  • Engaging using the right channel, at the right time with the right message
  • Predicting which customers may be at risk as well as the best way to retain them
  • Gaining a better awareness of customer needs, intentions and behaviors through social media
  • Maximizing customer lifetime value through personalized offers

Advanced Analytics and Contextual Cross-Selling

Successful customer acquisition and cross-selling has always depended on being able to deliver the best solution, at the most appropriate time, using the channel the prospect or customer prefers. Advanced analytics allows a bank marketer to not only identify potential sales opportunities more accurately, but to do so in real-time. In the best situation, advanced analytics will identify who may need a specific product or service before the customer knows this themselves.

In the past, the collection, cleansing, combination and enrichment of data was separate from the analysis process (which occurred at different periods after the fact). In many cases, the analysis was done as infrequently as monthly or even quarterly. This resulted in insights that were reactive as opposed to proactive.

According to IBM, “Streaming analytics and other real-time analysis capabilities gives [banks] a window into opportunities when and where they occur. Predictive analytics empower [a bank or credit union] to capture, examine and respond to relevant customer data at the point of interaction, at the moment of engagement, to optimize the customer experience and marketing and sales outcomes.” In other words, this more-informed and better-targeted approach lets an organization provide more relevant offers, thereby significantly boosting cross-sell and up-sell results.

Advanced Analytics and Multi-Channel Engagement

One of the added benefits of advanced analytics is the ability to embed the results of the analysis within both physical and digital delivery channels, as part of business processes and within operational systems. This enables a bank or credit union to deliver a consistent and optimized experience to each individual customer across an entire organization.

Customer-facing representatives can be equipped to provide the best response to a customer’s inquiry from both the organization’s and customer’s perspective. Analytics can also deliver messages using the channel most preferred by the customer as opposed to the channel most preferred by the financial institution.

Finally, detailed insights into individual and organizational behavior can enable an organization to proactively resolve issues that may impact a specific segment of the customer base. From interest rate changes to ATM outages, personalized communications can be delivered to micro-segments of customers to improve the overall customer experience.

Advanced Analytics and Social Data

To dig deeper into customer preferences, attitudes and behaviors, many financial organization integrate social media insights. Social media is not only an excellent source for consumer needs, but also significant life events. These added data sources make the power of advanced analytics and micro-segmentation even more powerful.

Social data is especially powerful in new customer acquisition. Beyond traditional tracking and credit bureau insights, social insights can provide a better perspective on people similar to current customers. By communicating using messages that resonate, results of marketing programs can be improved.

The Future of Advanced Analytics

“The potential of advanced analytics grows exponentially over time. Each iteration, additional data source and performance measurement results in learning that enhances the accuracy of the predictive models.”

The potential of advanced analytics grows exponentially over time. Each iteration, additional data source and performance measurement results in learning that enhances the accuracy of the predictive models. It also allows organizations to refine data sources as opposed to simply adding more and more data.

Finally, with each iteration, predictability goes up while costs can go down, improving marketing efficiency. From the customer’s perspective, the messaging in more “on target,” improving the customer experience, satisfaction and lifetime value.

According to IBM, “The use of new technologies such as the Internet of Things (IoT) and mobile beacons is attractive but they are not currently used in high volumes because companies recognize that they need to perfect the [data] basics first. There is too little integration between systems and data sets to begin introducing even more touchpoints and variables into the mix. There is still a great deal of scope to find growth in existing resources, if only companies are able to focus on improving their integration.”

Financial institutions that effectively leverage data and advanced analytics will be in a position to capitalize on newer technologies such as machine learning and automation. Those firms who fall behind will need to quickly overcome barriers that are preventing them from enjoying the benefits of advanced analytics or they will find themselves too far behind to catch up.

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